Who Should Bear the Risk? A Theoretical and Behavioral Investigation of After-Sales Service Contracts

Since downtime is expensive, it is key to use the right after-sales service contract to achieve high equipment availability. Resource-based contracts (RBCs) are common, but they fail to motivate suppliers to provide reliable products and services as suppliers are paid for their after-sales services. Performance-based contracts (PBCs) have been proposed as a way to solve this issue, as it shifts much of the downtime risk to the supplier by making him responsible for machine uptime, but then customers might reduce care efforts. We are the first to analytically incorporate the care in equipment availability. We propose the full-care contract (FCC) to achieve both high reliability and care, and maximize the chain efficiency. We find that only the FCC can achieve full chain efficiency. After discussing potential behavioral factors in this context, with a focus on risk aversion, we conduct a lab study with decision makers as suppliers. Experimental results confirm that the FCC achieves higher total profits than the PBC and RBC. We further find that subjects are more likely to switch from the RBC to the FCC than to the PBC, despite the higher risk involved in the FCC.Finally, we observe that effort levels set by suppliers are above normative predictions and we discuss potential explanations for this result

Multiperiod Inventory Management with Budget Cycles: Rational and Behavioral Decision-Making

We examine inventory decisions in a multiperiod newsvendor model. In particular, we analyze the impact of budget cycles in a behavioral setting. We derive optimal rational decisions and characterize the behavioral decision-making process using a short-sightedness factor. We test the aforementioned effect in a laboratory environment. We find that subjects reduce order-up-to levels significantly at the end of the current budget cycle, which results in a cyclic pattern during the budget cycle. This indicates that the subjects are short-sighted with respect to future budget cycles. To control for inventory that is carried over from one period to the next, we introduce a starting-inventory factor and find that order-up-to levels increase in the starting inventory

Development and analysis of the Soil Water Infiltration Global database.

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type (~40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making